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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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integrated with the NiMARE (NMA) software project. To be considered you will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain
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will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain imaging data and possess sufficient specialist knowledge in brain
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the challenge of time-consuming sideshaft testing. As a key member of the team, you will apply cutting-edge machine learning and deep learning techniques to dramatically reduce testing cycles. You will lead life
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team, you will apply cutting-edge machine learning and deep learning techniques to dramatically reduce testing cycles. You will lead life cycle analyses, implement advanced health monitoring strategies
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, artificial intelligence/machine learning, digital twins, and blockchain technology for operations and maintenance. This position is part of the RESTORE project, which aims to develop, test, and deploy
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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful
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language processing (NLP), large language models (LLMs), machine learning (ML), and data visualization. The candidate will leverage their expertise in AI, statistics, and programming to design, develop, and evaluate
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Overview Nature offers a mechanism - called homeostasis - by which life forms can maintain their physical integrity and well being. On the other hand, a series of machines, including robots, cannot